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Record W2379038617

The Analysis of 241 Health Claims in Chaoyang City from 2003 to 2005

2007· article· en· W2379038617 on OpenAlexaboutno aff
Tian Shu-yua

Bibliographic record

VenueYufang yixue luntan · 2007
Typearticle
Languageen
FieldHealth Professions
TopicMedical Malpractice and Liability Issues
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineSanctionsHygieneQuarter (Canadian coin)Public healthFamily medicineBusinessEnvironmental healthLawNursingPolitical science
DOInot available

Abstract

fetched live from OpenAlex

[Objective]To understand the contents and the way of consumers' claims,the key points and focus which mostly concerned by the consumers,to provide the basis for the administration of Public Health Department to make decisions,so that some effective supervision methods could be adopted to safeguard consumer's health and the legitimate rights and interests.[Methods]241 health claims treated in Chaoyang Institute for Health Inspection and supervision during 2003-2005 were analyzed.[Results]From 2003 to 2005,241 health claims had been reported to the Institute,of them 85 cases in 2003,74 cases in 2004,and 82 cases in 2005;156 cases of them were through phone call,48 cases of them were letters transferred from higher authority.9 cases of them were letters directly from consumers and 28 cases of them were from visiting consumers;140 cases of them were related to food hygiene,78 cases related to medical market,11 cases related to infectious diseases,12 cases related to environmental hygiene in public places.Of the 241 cases,118 cases were made administrative sanctions;57 cases were ordered to stop professional activities and be fined;19 cases were ordered to stop business and illegally obtained were confiscated,at the same time be fined;17 cases were ordered to stop profession,and confiscating drugs and the instruments,at the same time be fined;25 cases were fined only.[Conclusion]In the 3rd quarter of every year,the claims related to food hygiene and medical market were the main cases.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.223
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.066
GPT teacher head0.488
Teacher spread0.422 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2007
Admission routes1
Has abstractyes

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